OCR Tools

Open Climate Research is an ongoing project that aims to facilitate creative experimentation with modeled climate data. OCR Tools aims to be much more than a climate data viewer by enabling non-scientists to utilize a wide range of datasets and providing users with simple feedback conducive to learning. In addition to providing basic analysis functions, OCR Tools includes organizational and creative tools.

Installing / Getting started

Run the following to install:

pip install ocrtools

Examples

• Open a NetCDF dataset with

• import ocrtools as ocr
  cesm_TS = ocr.load('path/to/cesm_TS_data.nc', var='TS')

  If var is omitted, ocrtools will print out all variables in the dataset and ask you to specify a variable(s) of interest via command line. The dataset is then opened as an Xarray Dataset

• Create a scope object

  lima_peru = ocr.scope(location='Lima, Peru', yr0=1950, yrf=2000)

  • Location can also be specified by keyword arguments lat_min, lat_max, lon_min, and lon_max; or if none of these are given, location can be specified interactively by selecting areas on a map

• Subset your data

  lima_TS = ocr.subset(cesm_TS, lima_peru)

• Select an area on a map and take the spatial average

  from ocrtools import plt
  map_selection = ocr.scope()

  [OCR] Creating new scope object
  Enter yr0: 
  Enter yrf: 
  Select area(s) on map and close the pop-up window

  

[OCR] Finished writing new scope object

peru_TS = ocr.subset(cesm_TS, map_selection)
peru_avg_TS = ocr.spatial_average(peru_TS)
peru_avg_TS['TS'].plot()
plt.show()